:: ApplicationDeveloperApi ::
:: ApplicationDeveloperApi ::
:: ApplicationDeveloperApi ::
Operator that performs DBSCAN(Density-based spatial clustering of applications with noise). It groups points with nearby neighobors and makes as outlies points that are in low density region.
:: ApplicationDeveloperApi ::
:: ApplicationDeveloperApi ::
Operator that performs EM(Expectation–Maximization) Clustering. It performs two steps iteratively to partition into k clusters. Expectation step calculates the expected value of the log likelihood function and maximization step finds the parameter maximizing the expected log-likelihood.
:: ApplicationDeveloperApi ::
:: ApplicationDeveloperApi ::
Operator that makes equal-depth-binning. It divides the range into N intervals, each containing approximately same number of samples.
:: ApplicationDeveloperApi ::
:: ApplicationDeveloperApi ::
Operator that makes equal-width-binning. It divides the range into N intervals of equal size(uniform grid).
:: ApplicationDeveloperApi ::
:: ApplicationDeveloperApi ::
Operator that performs Generalized Linear Regression. It generalizes linear regression by associating linear model with response variables that have error distribution models through link function and the magnitude of variance.
:: ApplicationDeveloperApi ::
:: ApplicationDeveloperApi ::
Operator that performs K-Means clustering. It partitions n rows into k clusters in which each row belongs to the cluster with the nearest mean.
:: ApplicationDeveloperApi ::
:: ApplicationDeveloperApi ::
Operator that performs KMedoids clustering. It partitions the data set of n rows into k clusters. It chooses data points as centers and uses the Manhattan Norm to calculate distance between data points.
:: ApplicationDeveloperApi ::
:: ApplicationDeveloperApi ::
Operator that performs Linear Regression. It aims to model the relationship between two variables by fitting a linear equation to observed data.
:: ApplicationDeveloperApi ::
:: ApplicationDeveloperApi ::
Operator that imputes the missing values of a given dataframe according to the given condition.
:: ApplicationDeveloperApi ::
Operator that performs Agglomerative clustering. It aims to make a hierarchy of clusters in bottom-up approach. Each observation begins with its own cluster and pairs of clusters are combined as the hierarchy goes up.